In this dissertation, we explored multiple coding techniques to reduce energy consumption, improve performance, and secure wireless sensor networks specifically and ad-hoc networks in general. With the introduction of Internet of Things (IoT) and 5G technologies, wireless sensor networks are quickly emerging as an important and key technology in the...
Newcomers’ seamless onboarding is important for open collaboration communi- ties, particularly those that leverage outsiders’ contributions to remain sustainable. Nevertheless, previous work shows that OSS newcomers often face several barriers to contribute, which lead them to lose motivation and even give up on contributing. A well-known way to help newcomers...
The ubiquity of high quality video and proliferation of mobile devices has contributed to an unprecedented rise in video consumption. HTTP, in conjunction with adaptive streaming, has become the de facto mechanism for delivering the vast majority of video as it readily caters to heterogeneous networks and devices. This dissertation...
Wave energy is a potentially important renewable clean source of energy that can help solve the energy demand throughout the world. A great deal of research has been conducted in the last few decades and it is now reaching the point of full implementation. In order to compete with other...
Our goal is to build a system to model the RNA sequences that reveals their structural information by using efficient dynamic programming algorithms and deep learning approaches. We aim to 1) achieve linear-time for RNA secondary structure prediction based on existing minimum free energy models; 2) utilize deep neural networks...
Many database users are not familiar with formal query languages, the concept of schema, or the exact content of their database. Thus, it is challenging for these users to formulate their information needs over semi-structured and structured databases. To address this problem, researchers have proposed usable query interfaces over which...
As a general solution to the problem of managing structural and content variability in relational databases, in previous work we have introduced the Variational Database Management System (VDBMS). VDBMS consists of a representation of a variational database (VDB) and a corresponding typed query language (v-query). However, since this is a...
Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
This dissertation focuses on the application of diatom frustules, the biosilica shell of an algae possessing physical and photonic properties capable of enhancing optical signals, for the enhancement of optical sensing. In this work, we incorporate diatom frustules into biosensors for signal enhancement and improved target molecule detection. The potential...
More and more people have incorporated GIF in their messaging these days and often send gif as a reply. GIF is Graphics Interchange Format and is a short-animated picture without a sound. Searching a trivial gif with a regular emotion is easy to find but if some iconic expression is...
Successive-approximation-register (SAR) analog-to-digital converters are popular for medium accuracy, medium speed and low power applications, such as in biomedical applications. They have low latency and simple architecture compared with ΔΣ ADCs. This is because of SAR ADCs’ binary searching scheme. Furthermore, SAR ADCs can apply oversampling and noise shaping schemes...
Accurate information of power network parameters is essential for performing various power system monitoring and control tasks including state estimation, economic dispatch, and contingency analysis. In this paper, we present a novel approach of power network parameter correction wherein we exploit the sparse nature of parameter errors. Parameter error correction...
Crowdsourcing is a popular paradigm to address the high demands for labeled data in big data deluge. It aims to produce accurate labels by effectively integrating noisy, non-expert labeling from crowdsourced workers (annotators). The machine learning community has been studying effective crowdsourcing methods for many years, and many models and...
In a power system, operators maintain voltage stability through adequate reactive reserves. Maintaining and accessing an efficient allocation of reactive reserves is prohibitively complex because of reactive line losses, the variety of reactive resources, and either limited or variable reactive outputs from renewable sources. By clustering the system into smaller...
Metal-insulator-metal (MIM) and dual-insulator MIM (MIIM) devices are used in rectennas, hot-electron transistors, single electron transistors, resistive random access memory (RRAM), and capacitors. The performance of these devices relies heavily on the energy barrier height at each metal-insulator interface. Thus, determination of the in-situ electron energy barrier at each interface...
Learning Analytics and other branches of Educational Research such as Computing Education Research (CER) implicitly assume that students, especially college students, have no barriers to access learning platforms or software packages. This assumption may be attributed to such pervasive beliefs such as "everyone has a device", or "everyone can access...
Building software systems that adapt to the changing environment is challenging. Developers cannot anticipate all the changes in advance, and even if they could, the effort required to handle such situations is too onerous for practical purposes. Self Adaptive Software (SAS) adapts itself as per changing environment. The area of...
Humans are remarkably efficient in learning by interacting with other people and observing their behavior. Children learn by watching their parents’ actions and mimic their behavior. When they are not sure about their parents demonstration, they communicate with them, ask questions, and learn from their feedback. On the other hand,...
Over the last decades, CMOS-integrated sensors have made impressive progress in performance, form-factor, and energy-efficiency for various applications such as imaging, physical/chemical sensing, bio/health monitoring. In the era of the artificial intelligence (AI) and the internet-of-things (IoT), such CMOS-integrated sensors are essential for massive and comprehensive data acquisition, where sensing...
In today’s world, we are highly dependent on software systems together with devices for almost every task in our day to day life. Software system upgrades are released whenever it is necessary to accommodate the ever-changing user’s needs. The devices we use to run the software systems might be of...
Harvesting energy from ambient sources can provide power autonomy to energy efficient electronics and sensors. The last decade has seen a multitude of ways to scavenge energy from various sources like solar, thermal, electromagnetic, electrostatic, piezo-electric and many more. Thermal energy from human body heat is ubiquitous and can be...
Most database users do not know formal query languages, such as SQL, and prefer to express their information needs using usable query languages, such as keyword queries. Keyword queries, however, are inherently ambiguous and challenging for the database systems to understand and answer effectively. We propose a novel approach to...
This research focuses on receiver architectures which enable better spectral eciency
by handling blockers in the same spectral range as the signal. The presence of
such blockers, without the use of blocker cancelling/ltering techniques leads to gain
compression and hence, consequent performance degradation of receivers leading to
reduced spectrum...
Scientists and engineers have to analyze and query multiple large databases. Analysis over databases created by phasor measurement units can provide insight into the health of the grid, thereby improving control over operations. Realizing this data-driven control, however, requires validating, processing and storing massive amounts of PMU data efficiently, which...
An innovative silver nano-dimple arrays (Ag DAs)-integrated microfluidic device was developed to achieve highly sensitive fluorescence-based nucleic acid detection. The Ag DAs were utilized to produce surface plasmon resonance (SPR) for strong fluorescence enhancement. We systematically investigated the plasmon-enhanced fluorescence by controlling the nanostructure dimension of the Ag DA substrate....
This thesis studies the problem of structured prediction (SP), where the agent needs to predict a structured output for a given structured input (e.g., Part-of-Speech tagging sequence for an input sentence). Many important applications including machine translation in natural language processing (NLP) and image interpretation in computer vision can be...
Narratives are central to communication and the human experience. For a computer system to understand a narrative, it must be able to identify the key facts or plot elements that describe what happened or how the world has changed. These element are called events;establishing a document’s events and the relationships...
The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
Automatic music transcription (AMT) is the task, given an acoustic representation of music, to recover a symbolic notation of the written notes expressed by the sound. Transcribing music with multiple notes sounding simultaneously is difficult for both humans and machines. Much existing work on AMT has focused on suitable acoustic...
The increased demand for building materials that are friendly to the environment, along with the latest advances in wood science and technology, which exploit the fiber orientation of wood, resulted in composite wood materials known as mass-timber products. To understand the effects the wood fiber orientation has on the dynamic...
Traditional bus-based interconnects are simple and easy to implement, but the scalability is greatly limited. While router-based networks-on-chip (NoCs) offer superior scalability, they also incur significant power and area overhead due to complex router structures. In this thesis, a new class of on-chip networks, referred to as Routerless (RL) NoCs,...
Wearable sensors with an inertial measurement unit (IMU) are popular for indoor positioning and activity pattern detection. The IMUs can be connected to a wireless transmission module, allowing users to monitor and process motion-related parameters remotely. Because of the complexity and uncertainty of signals in indoor environments, a radio frequency...
Spreadsheets are a pervasive technology throughout personal and industrial use. Often times, the user is not the author, contributing to a lack of understanding of the purpose and functionality of a spreadsheet. Furthermore, the lack of understanding is a major reason for mistakes in the use and maintenance of spreadsheets....
This thesis deals with target localization using multiple-input multiple-output (MIMO) radars. In the field of communications, navigation, radar, and sensing networks, one of the common and most sophisticated problems is target localization. We develop a target localization scheme in distributed MIMO radar systems using bistatic range measurements. The localization approach...
One goal of using robots in introductory computer science (CS) courses is to improve motivation among learners. In this study, we investigate the effectiveness of using the Cozmo and Lego Mindstorm robots to improve students’ motivation in a CS orientation course, and we describe our experience using these robots in...
Anomaly detection has been used in variety of applications in practice, including cyber-security, fraud detection and detecting faults in safety critical systems, etc. Anomaly detectors produce a ranked list of statistical anomalies, which are typically examined by human analysts in order to extract the actual anomalies of interest. Unfortunately, most...
Traditional approaches to streaming H.264 video over a network typically rely on a single method of transport (i.e., reliable or unreliable) and/or use static values for parameters that can have a significant negative impact on the perceptual quality of the received video. This dissertation presents a dynamic method for wireless...
Load flow studies are one of the most essential engineering applications for grid operators because they provide a clear picture of the operating conditions of the power system. Traditionally, the load flow problem is assumed to be deterministic; that is, the system variables contain no randomness. Unfortunately, this assumption is...
The Jetson Artificial Intelligence Tool chain (JAI-TC) is a set of packages, APIs and libraries for Artificial Intelligence applications to be deployed on the NVidia SOC, Jetson TX2. JAI-TC automates the installation of these items allowing for a wider set of users to leverage these technologies. Prior to this, the...
We consider the problem of computing the cannonical polyadic decomposition (CPD) for large-scale dense tensors. This work is a combination of alternating least squares and fiber sampling. Data sparsity can be leveraged to handle large tensor CPD, but this route is not feasible for dense data. Inspired by stochastic optimization's...
Modern communication systems often have the ability to transmit signals on multiple communication mediums (e.g., RF, visible light) or interfaces (e.g., MAC layer protocols) at the same time. While each channel has different characteristics, a centralized controller with channel condition information will be able to schedule the resource allocated to...
While electrification is currently one of the largest trends in the automotive world, other related industries are also evaluating electrification opportunities as a means to reduce environmental impact, emissions, and noise pollution. One such sector is the aviation industry. While it is generally accepted that all-electric aircraft are not a...
Structural health monitoring (SHM) systems perform automated non-destructive damage detection and characterization for a variety of large structures including civil structures such as bridges and aerospace structures such as aircrafts and space vehicles. The goals of SHM include preventing catastrophic structural failures, increasing reliability, reducing maintenance costs, and increasing the...
This work demonstrates correlation of microwave signals encoded with 16-bit codes using the parametric interaction of spin waves. Signal processing correlators are devices that compare two signals, such as a reference code and a received code, where the output indicates the similarity between the signals. Correlators are used in communication...
Learning novel concepts from relational databases is an important problem with applications in several disciplines, such as data management, natural language processing, and bioinformatics. For a learning algorithm to be effective, the input data should be clean and in some desired representation. However, real-world data is usually heterogeneous – the...
There are nearly two million limb amputees living in the United States of America. Loss of limbs results in profound changes in one's life. However, the underlying neural circuitry and much of the ability to sense and control movements of their missing limb is retained even after limb loss. This...
Although the need for gender-inclusivity in software itself is gaining attention among both SE researchers and SE practitioners, and methods have been published to help, little has been reported on how to make such methods work in real-world settings. For example, how do busy software practitioners use such methods in...
This report presents an efficient method for semi-supervised video object segmentation – the problem of identifying foreground pixels occupied by a target object. The target is specified by the ground-truth mask in the first video frame. While the state of the art achieves a segmentation accuracy greater than 80%, it...
Conventional Delta-Sigma analog-to-digital converters (ADCs) utilize operational transconductance amplifiers (OTAs) in their loop filter implementation followed by multi-bit voltage domain quantizers. As CMOS integrated circuit technology scales to smaller geometries, the minimum transistor length and the intrinsic gain of the transistors decrease. Moreover, with process scaling the voltage headroom decreases...
As the power system grows larger and more complex, real-time monitoring and control become very significant in order to achieve reliable operation of the power system. Before any security assessment can be made or control actions are taken, the reliable estimate of the existing state of the system must be...
In recent years, SAR ADCs have been shown to acheive faster conversion times and improved power efficiencies due to their simple building blocks that are digital in nature and scale favorably with technology. High resolution ADCs with stringent noise requirement has led to the adoption of hybrid ADC architectures such...
In this research, we address the problem of learning a single causal network structure from multiple dataset generated from different experiments. The experiments can be observational or interventional. We assume that each dataset is generated by an unknown causal network altered under different experimental conditions (interventions, manipulation or perturbation). As...
As the number of wireless devices, the demand for high data rates, and the need for always-on connectivity are growing and becoming more stringent with the evolvement and emergence of 5G systems, network engineers and researchers are being faced with new unique challenges that need to be addressed. Among many...
Low-power millimeter-wave (mm-wave) transceivers are of interest for achieving energy-efficient high data rate short-reach wireless and guided-wave links.
Spatial modulation or space-shift keying (SSK) can provide energy efficiency improvements by using antenna-switching or transmission direction switching for data modulation. Such links are particularly attractive at millimeter-wave frequencies due to small...
With the rapid growth of worldwide internet traffic in data centers and clouds, silicon photonics has been utilized to provide enormous data bandwidth and outstanding energy efficiency over electronics. Computing servers and storage servers that are connected by communication links are relying more on optical rather than electrical means mainly...
Efficient time-series analysis can impact multiple application domains such as motif discovery in gene analysis or music data, extracting spectro-temporal patterns in acoustic scene analysis, or annotating and classifying electrical bio-signals (such as ECG, EEG, and EMG) for medical applications.
Time-series analysis involves a variety of tasks.
To predict future...
Millimeter-wave (mm-wave) technology promises high speed, high system capacity and low latency interconnects with reduced cost. Applications like high data-rate wireless links, next generation automotive sensors and security body scanners highly depend on mm-wave technology innovations. As operating frequency moves to higher mm-wave bands, shrinking antenna dimensions enable co-integration of...
In any biomedical signal acquisition system, a front-end amplifier is needed to amplify low amplitude bio-signals while filtering out any unwanted low-frequency artifacts. The design of low frequency poles within the sub-Hz range implies very large time-constants which goes against system integrability. In recent years, the pseudo resistor has been...
The CMOS two-stage Operational Transconductance Amplifier (OTA) has been a key enabler for mixed-signal IC design for nearly four decades . This research focuses on a modified two-stage CMOS OTA that features load-pole cancellation (LPC); i.e., the resulting architecture is essentially a two-stage CMOS OTA with no load capacitance. The...
The Pacific Northwest is part of the "Ring of Fire," which is well-known for heavy seismic activity. Numerous active faults in the area have encouraged electric grid managers in the region to more deeply contemplate and proactively intervene to support grid resilience. This research introduces Monte Carlo (MC) based power...
This dissertation focuses on indoor free-space optical communications systems for use in short range wireless networks. We propose that current radio frequency wireless links be augmented or replaced with optical frequency links due to overcrowding in the radio frequency spectrum. Optical frequencies contain hundreds of terahertz of unregulated bandwidth and...
The energy barrier heights between two recently reported Ta-based amorphous metals (TaWSi and TaNiSi), TaN, and atomic layer deposited Al2O3 and HfO2 insulators are measured in metal/insulator/metal (MIM) structures with Au top electrodes using internal photoemission (IPE) spectroscopy. For Al2O3, the Ta-based metal barrier heights, phi(Bn), increase with increasing metal...
Due to the continued evolution of 5G standards, the need for higher rates of data, lower latency network access, and implementations that are more energy efficient have become clear. To enable wireless communications at rates over tens of Gbps, the wide bandwidth of mmWave spectrum can be exploited. Beamforming (or...
In Earth science, we must often collect data from sensors installed in remote locations. Retrieving these data and storing them can be challenging. Present options include proprietary commercial dataloggers, communication devices, and protocols with rigid software and data structures that may require ongoing expenses. While there are open-source solutions that...
Deep learning and neural network has been widely used in research, deep learning has empowered many tasks such as point clouds segmentation and shape recognition. One of the main advantages of deep interaction point cloud segmentation is that it allows the feature extraction can be learned through neural network based...
People like going on trips with friends and tend to plan their trips well in advance to have the best possible experience of a destination and get the most out of the places they visit and/or the activities they plan to partake in. Right now, the Internet provides a wealth...
Movement pattern detection can be applied in a variety of applications such as assisting independent living of seniors at home, behaviour understanding in surveillance systems, sports analytics, and robotics. This project develops a scheme that fuses information from different sensors to detect movement patterns. This report contains three main parts:...
New MS in CS students in the Electrical Engineering and Computer Science school at OSU are required to file their Program of Study by the end of their 2nd term. Many of them, especially international students, are in a totally new ecosystem, so they find it overwhelming to choose the...
RNA structure prediction is a challenging problem, especially with pseudoknots. Recently, there has been a shift from the classical minimum free energy-based methods (MFE) to partition function-based ones that assemble structures based on base-pairing probabilities. Two typical examples of the latter group are the popular maximum expected accuracy (MEA) method...
Using robotics in education allows students to become familiar with multiple topics in science, technology, engineering, and mathematics (STEM). With the use of robotic educational tools in the 8th – 12th grade classrooms, such as Sphero, Anki Cozmo, and Lego Mindstorms, few devices allow students to build the robots’ electrical...
Ring amplifiers (ringamps) have shown excellent power efficiency in the latest state-of-the-art analog to digital converters (ADCs). This thesis describes circuit techniques to ensure robust operation of ringamps using standard analog techniques and proportional-integral-derivative(PID) controller analogy. Large-signal and small-signal analysis of a ringamp are performed using simple RC settling and...
How should reinforcement learning (RL) agents explain themselves to humans not trained in AI? To gain insights into this question, we conducted a 124 participant, four-treatment experiment to compare participants’ mental models of an RL agent in the context of a simple Real-Time Strategy (RTS) game. The four treatments isolated...
The rapid population growth in large urban cities has led to an unprecedented increase in both the number and the diversity of wireless devices and applications with varying quality of service requirements in terms of latency and data rates. LinkNYC is an example of an urban communication network infrastructure, which...
Although deep reinforcement learning agents have produced impressive results in many domains, their decision making is difficult to explain to humans. To address this problem, past work has mainly focused on explaining why an action was chosen in a given state. A different type of explanation that is useful is...
Information Foraging Theory (IFT) has successfully explained how people seek information in various domains, in turn, informing the design of several tools and information-intensive environments. However, prior research has not explored foraging in the presence of several, very similar variants of the same artifact. Such variants are commonplace in several...
As the sources of our electricity shift from centralized and carbon emitting, to a portfolio of distributed, clean-energy sources, the wave energy converter (WEC) has become a topic of exploration and development for providing coastal communities electric power. Part of this trend has included an effort to create open source...
Data acquisition (DAQ) systems are a necessary component for products whose outcomes depend on collected information throughout its operation. Current systems are directed towards users utilizing custom hardware, software, and requiring its user to have high-level skills in coding and system setup; but with the increasing interest in renewable energy,...
Deep Learning methods have been gaining a lot of significance for various Biomedical applications for diagnosing several types of diseases. Two applications considered here are: 1) Diabetic Retinopathy Detection and 2) ECG signal Classification (or Arrhythmia Detection). Diabetic Retinopathy (DR) is a major cause of blindness in Diabetic patients, and...
Question answering forums like Reddit have been quite effective in improving social interaction and disseminating useful information. Community members ask a variety of questions related to a subject which are answered by other community members. The answers are given ratings by other members. In this thesis we study the problem...
To users, mobile touchscreen devices have appealing characteristics; among these characteristics is intuitiveness, which leads to mobile devices being used almost everywhere by almost everyone to accomplish almost anything. This statement, to some degree, holds for children too. Despite touchscreen devices’ intuitiveness and popularity, we don’t know much about how...
Heatmap regression has became one of the mainstream approaches to localize facial landmarks. As Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) are becoming popular in solving computer vision tasks, extensive research has been done on these architectures. However, the loss function for heatmap regression is rarely studied. In...
This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
In this thesis, we propose a Blockchain-based distributed protocol for enabling deployment of dynamic, on-demand IoT networks. Specifically, the proposed protocol leverages Blockchain technology to: (i) enable distributed and secure authentication, registration, and management of IoT devices; (ii) provide fast discovery of IoT resources and scalable and secure instantiation of...
The thesis focuses on the development of a novel printed resistive humidity sensor and integrated flexible electronics for an RFID-enabled humidity sensing platform. We explored a hybrid nanocomposite material for humidity sensing consisting of carbon nanomaterials, conductive polymer and cellulose polymer that undergoes resistance change in response to humidity change....
The increasing demand for higher data-rates is challenging to satisfy with spectrum-deficient indoor WiFi networks. A novel hybrid WiFi Free-Space Optical (WIFO) system has been proposed to enhance the wireless capacity of indoor WiFi networks. In this thesis, an integrated optical wireless receiver is designed and integrated in 65-nm CMOS...
Ocean waves provide a promising source of renewable energy for the North American electric grid. However, ideal control of wave energy converters (WECs) requires perfect forecasting of future wave conditions, and waves can be unpredictable. This paper presents a comparison of three different prediction methods and analyzes their performance in...
Noise-shaping multibit quantizers in a ΔΣ modulator offer extra orders of noise shaping without increasing the loop-filter order and without compromising the stability of the modulator. This dissertation presents two new architectures for improving the overall performance of continuous-time ΔΣ modulators using noise-shaped quantizers.
The first modulator architecture is motivated...
Computer science is, at its core, about solving problems. The "Carry out the Plan" portion of problem solving is often examined and emphasized in CS 1 and CS 2, forgetting to emphasize the other important aspects of the problem solving process. This study focuses on the other problem-solving steps, which...
Ring amplification has emerged as an efficient technique to drive large capacitive loads in switched capacitor circuits. We propose circuit techniques to demonstrate the first application of a ring amplifier in a non-capacitive feedback system of a LDO. These techniques enable a simple cap-less LDO structure in 180nm CMOS that...
In open set recognition, a classifier must label instances of known classes while detecting instances of unknown classes not encountered during training. To detect unknown classes while still generalizing to new instances of existing classes, this thesis introduces a dataset augmentation technique called counterfactual image generation. This approach, based on...
Deep neural networks currently comprise the backbone of many applications where safety is a critical concern, for example: autonomous driving and medical diagnostics. Unfortunately these systems currently fail to detect out-of-distribution (OOD) inputs and can be prone to making dangerous errors when exposed to them. In addition, these same systems...
Filters and data converters are key analog-and-mixed-signal (AMS) building blocks in communication systems, such as software-defined radios and internet-of-things. In this dissertation, novel switched-capacitor filter and analog-to-digital converter (ADC) circuit configurations have been explored which are power efficient and are digital scaling friendly.
First, a novel switched-capacitor low-pass filter architecture...
The machine learning and deep learning models have been very lightly explored in analyzing the behavior of On-Chip network traffic. These models have proven their potential in pattern recognition, classification etc... In this paper we analyze the spatial pattern that each workload exhibits in its life cycle during execution. We...
We consider multiple Compressive Sensing (CS) problems wherein the supports of signal vectors of CS problems are restricted to satisfy a collection of joint logical constraints, which we refer to as coupling constraints. We consider a case where the coupling constraints are encoded in a graph and present a sequential...
Portable, high power efficiency communication devices is a growing market in the semiconductor industry. Analog-to-digital converters (ADC) are key interface that are used to digitize the sensed information. Recently, digital techniques have been proposed to improve analog building block power efficiency in sub-micron technologies. This research focuses on mixed signal...
There are growing interests in designing polynomial-time approximation schemes (PTAS) for optimization problems in planar graphs. Many NP-hard problems are shown to admit PTAS in planar graphs in the last decade, including Steiner tree, Steiner forest, two- edge-connected subgraphs and so on. We follow this research line and study several...
Direct sequence spread spectrum (DSSS) was initially used for anti-jamming in military applications and was later developed in other commercial applications. Walsh codes, which are a set of mutually orthogonal codes, are one type of the spreading codes used in DSSS systems. For any spreading codes of length N, these...
Cryptographic obfuscation is a powerful tool that makes programs “unintelligible” yet still runnable. It essentially gives programs the ability to keep secrets. The practical applications of obfuscation range from keeping secrets in banking applications to preventing software theft to providing secure messaging applications. The cryptographic applications of obfuscation are also...
Most tasks in natural language processing (NLP) involves structured information from both input (e.g., a sentence or a paragraph) and output (e.g., a tag sequence, a parse tree or a translated sentence). While neural models achieve great successes in other domains such as computer vision, applying those frameworks to NLP...
Real time indoor positioning awareness systems aim to add localization capabilities to upcoming wireless technologies that are quickly becoming an important feature for indoor environment. RF-based impulse-radio ultra-wideband (IR-UWB) is a promising technology for in-door positioning systems due to obstacle penetration capabilities, immunity to multi-path and fading, and high resolution....